Linuxfabrik Python Libraries

Python 3.9+ modules for Linuxfabrik projects: DB access, SQLite KVS caching, WinRM, SMB, shell execution, 15+ API integrations (Icinga2, Veeam, Nextcloud, ...). Available on PyPI. • made by Linuxfabrik

Linuxfabrik Python Libraries

A mature, production-grade Python library collection providing 40 modules with 300+ functions for system administration, monitoring, and infrastructure automation. These libraries are used across several Linuxfabrik projects -- most prominently the Linuxfabrik Monitoring Plugins (Nagios/Icinga check plugins), but also in ChecklistFabrik and other tools.

If these libraries help you developing your own monitoring plugins, system tools or infrastructure automation, please give it a star.

The library requires Python 3.9+ and runs on every platform.

Documentation

Full documentation is available at linuxfabrik.github.io/lib. It is automatically built and deployed on every push to main.

Installation

Add linuxfabrik-lib as a dependency to your project, or install it manually:

pip install --user linuxfabrik-lib

Design Principles

These libraries are built with a clear set of priorities:

• Procedural by design. The libraries deliberately use a procedural/functional style rather than object-oriented programming. Pure functions with explicit inputs and outputs are easier to read, test, and reason about. This is especially true for the most prominent use case -- monitoring plugins -- which are short-lived, linear processes with no complex state to manage over time, where unnecessary abstraction layers would add overhead without tangible benefit.
• Broad compatibility. Python 3.9+ is the minimum, ensuring the libraries work on RHEL 8 and every major distribution without requiring newer runtimes.
• Cross-platform. Core functions behave identically on Linux, Windows, and macOS. Platform-specific code (WinRM, PowerShell, SMB) is cleanly separated.
• Minimal dependencies. We avoid pulling in large dependency trees. External packages are used only when the alternative would be unreliable or significantly more complex.
• Consistent error handling. Most functions return (success, result) tuples. The caller decides whether to continue or exit -- the library never exits on its own. The base.coe() ("Continue or Exit") helper makes this pattern concise.
• Automatic redaction. Sensitive data (passwords, tokens, API keys) in error messages is automatically sanitized before output.
• Nagios/Icinga conventions. State constants, threshold evaluation, performance data formatting, and range parsing follow the Monitoring Plugins Development Guidelines.
• Defensive defaults. Functions use sensible timeouts, safe SSL settings, and locked-down defaults so that plugins work out of the box without extensive configuration.

Library Index

Core Utilities

Data Access & Caching

System & OS

Networking & HTTP

Windows Integration

API Integrations

Usage Example

A typical monitoring plugin using these libraries:

import lib.args
import lib.base
import lib.url
from lib.globals import (STATE_CRIT, STATE_OK, STATE_UNKNOWN, STATE_WARN)

def main():
    # Parse arguments with custom threshold types
    parser = lib.args.ArgumentParser()
    parser.add_argument('--url', required=True)
    parser.add_argument('--warning', type=lib.args.float_or_none, default=80)
    parser.add_argument('--critical', type=lib.args.float_or_none, default=90)
    args = parser.parse_args()

    # Fetch data (coe = "Continue or Exit")
    result = lib.base.coe(lib.url.fetch_json(args.url))

    # Evaluate thresholds
    state = lib.base.get_state(result['usage'], args.warning, args.critical)
    perfdata = lib.base.get_perfdata('usage', result['usage'], '%', args.warning, args.critical, 0, 100)

    # Output and exit
    lib.base.oao('Usage is {}%'.format(result['usage']), state, perfdata)

if __name__ == '__main__':
    main()

Tips & Tricks

Count the function calls to any "lib" library in your project and sort by frequency:

grep -rhoP '\Wlib\.[a-zA-Z0-9_\.]+' * | sed 's/^[^a-zA-Z0-9]*//' | sort | uniq -c | sort -nr